电力系统保护与控制2025，Vol.53Issue(11)：63-71,9.DOI:10.19783/j.cnki.pspc.240660
基于多V-I轨迹融合的非侵入式负荷识别方法
Non-intrusive load identification method based on multiple V-I trajectory fusion
摘要
Abstract
In the field of load identification,it is difficult to effectively distinguish loads with similar trajectories using a single load feature.To address this issue,a non-intrusive load identification method based on multiple V-I(voltage-current)trajectory fusion is proposed.This method first preprocesses high-frequency sampling data to extract the fundamental voltage(V1),fundamental current(I1),and maximum harmonic current(Ih max).Subsequently,the fundamental voltage is combined with the fundamental current and maximum harmonic current to construct V1-I1 trajectories and V1-Ih max trajectories.Finally,these two trajectory features are input into a two-dimensional convolutional neural network(2DCNN)for load classification.Validation using the public PLAID and WHITED datasets shows that the proposed load identification method achieves accuracies of 99.66％and 99.81％,respectively.These results indicate that the proposed method not only enriches the information used for classification but also significantly improves load identification accuracy,demonstrating its practical application value in power monitoring and load management.关键词
非侵入式负荷识别/相似轨迹/V1-I1轨迹/V1-Ih max轨迹/卷积神经网络Key words
non-intrusive load identification/similar trajectories/V1-I1 trajectory/V1-Ih max trajectory/convolutional neural network引用本文复制引用
程志友,胡乐乐,陈思源,杨猛..基于多V-I轨迹融合的非侵入式负荷识别方法[J].电力系统保护与控制,2025,53(11):63-71,9.基金项目
This work is supported by the National Natural Science Foundation of China(No.6227020935). 国家自然科学基金项目资助(6227020935) （No.6227020935）
安徽省科技重大专项资助(18030901018) （18030901018）
